antirez's h3.c: Running MiniMax-H3 Video Generation Natively on Apple Silicon
Antirez/h3.c: MiniMax H3 inference engine for Mac computers
Antirez's h3.c is a native MiniMax-H3 inference engine for Apple Silicon, implementing prompt-to-video generation with Metal performance optimizations. It supports interactive sessions, first/last-frame conditioning, and Ref2VA references. The project offers a range of speed/quality presets, from a fast 4-step mode that generates a 22-frame video in about 3.5 seconds on M5 Max, to a close-to-reference 50-step mode. It also includes token reduction, internal canvas scaling, and automatic RoPE adaptation for 256x256 output.
The four-pass denoise took about 3.5 seconds on M5 Max, versus 26.4 seconds for the reference.
- Meleagris
I've been using MiniMax H3 on my M5 Pro 64GB MacBook Pro through ComfyUI. It works extremely well.
I had to modify the default ComfyUI workflows to use a GGUF quant (city96's ComfyUI-GGUF custom node, UnetLoaderGGUF in place of the stock loader) [0].
I use the model labeled Q5_K_M. There is Q8_0 available as well, which is 34GB and fits fine in 64GB unified memory if you keep resolution modest.
The main issue is speed, a ~9-second 480x864 clip at 20 steps takes me a bit over an hour. So this will be cool to try for the speed up alone.
There's a lot of great information and workflows available to follow on the r/StableDiffusion subreddit.
[0] https://huggingface.co/Abiray/MiniMax-H3-GGUF/tree/main/unet
- antirez
In the AMA Minimax said that H3 could support sparse attention, that would be a huge speedup! I wonder if there are any news on that. H3 is very cool. EDIT: testing a --sparse-attention optional mode based on what they said in the Reddit post.
- linzhangrun
On my 128GB M4 Max Mac Studio, generating a 15s 480p video with MiniMax H3 in ComfyUI takes an hour and a half.
Put Codex to work on deploying it now, hoping the speed can improve quite a lot :-) Thanks anyway
- diddid
This is where the DGX spark makes up a bit of the ground it loses on llm work, diffusion and cuda go together like peanut butter and jelly.
- TechSquidTV
This still requires 128Gb of memory, right? Me and my lowly 96Gb, like a commoner; missing out on the fun.